Sunday, 18 October 2015

In
this paper, a three-layer framework is proposed for mobile data collection in
wireless sensor networks, which includes the sensor layer, cluster head layer,
and mobile collector (called SenCar) layer. The framework employs distributed
load balanced clustering and dual data uploading, which is referred to as
LBC-DDU. The objective is to achieve good scalability, long network lifetime
and low data collection latency. At the sensor layer, a distributed load
balanced clustering (LBC) algorithm is proposed for sensors to self-organize
themselves into clusters.

In
contrast to existing clustering methods, our scheme generates multiple cluster
heads in each cluster to balance the work load and facilitate dual data
uploading. At the cluster head layer, the inter-cluster transmission range is
carefully chosen to guarantee the connectivity among the clusters. Multiple
cluster heads within a cluster cooperate with each other to perform
energy-saving inter-cluster communications. Through intercluster transmissions,
cluster head information is forwarded to SenCar for its moving trajectory
planning. At the mobile collector layer, SenCar is equipped with two antennas,
which enables two cluster heads to simultaneously upload data to SenCar in each
time by utilizing multi-user multiple-input and multiple-output (MU-MIMO)
technique. The trajectory planning for SenCar is optimized to fully utilize
dual data uploading capability by properly selecting polling points in each
cluster. By visiting each selected polling point, SenCar can efficiently gather
data from cluster heads and transport the data to the static data sink.
Extensive simulations are conducted to evaluate the effectiveness of the
proposed LBC-DDU scheme. The results show that when each cluster has at most
two cluster heads, LBC-DDU achieves over 50% energy saving per node and 60%
energy saving on cluster heads comparing with data collection through multi-hop
relay to the static data sink, and 20% shorter data collection time compared to
traditional mobile data gathering.

Aim

The
main aim is to achieve good scalability, long network lifetime and low data
collection latency by employs distributed load balanced clustering and dual
data uploading, which is referred to as LBC-DDU.

Scope

The
scope is to frame a three-layer framework is proposed for mobile data
collection in wireless sensor networks, which includes the sensor layer,
cluster head layer, and mobile collector (called SenCar) layer.

Existing
System

Sensors
are generally densely deployed and randomly scattered over a sensing field and
left unattended after being deployed, which makes it difficult to recharge or
replace their batteries. After sensors form into autonomous organizations,
those sensors near the data sink typically deplete their batteries much faster
than others due to more relaying traffic. When sensors around the data sink
deplete their energy, network connectivity and coverage may not be guaranteed.
Due to these constraints, it is crucial to design an energy-efficient data
collection scheme that consumes energy uniformly across the sensing field to achieve
long network lifetime. Furthermore, as sensing data in some applications are
time-sensitive, data collection may be required to be performed within a
specified time frame. Therefore, an efficient, large-scale data collection
scheme should aim at good scalability, long network lifetime and low data
latency.

Disadvantages

·The
proliferation of the implementation for low-cost, low-power, multifunctional
sensors has made wireless sensor networks (WSNs) a prominent data collection
paradigm for extracting local measures of interests. In such applications,
sensors are generally densely deployed and randomly scattered over a sensing
field and left unattended after being deployed, which makes it difficult to
recharge or replace their batteries.

·After
sensors form into autonomous organizations, those sensors near the data sink
typically deplete their batteries much faster than others due to more relaying
traffic. When sensors around the data sink deplete their energy, network
connectivity and coverage may not be guaranteed.

·Due
to these constraints, it is crucial to design an energy-efficient data
collection scheme that consumes energy uniformly across the sensing field to
achieve long network lifetime

Proposed
System

First,
we propose a distributed algorithm to organize sensors into clusters, where
each cluster has multiple cluster heads. In contrast to clustering techniques
proposed in previous works, our algorithm balances the load of intra-cluster
aggregation and enables dual data uploading between multiple cluster heads and
the mobile collector. Second, multiple cluster heads within a cluster can
collaborate with each other to perform energy-efficient intercluster
transmissions. Different from other hierarchical schemes, in our algorithm,
cluster heads do not relay data packets from other clusters, which effectively
alleviates the burden of each cluster head. Instead, forwarding paths among clusters
are only used to route small-sized identification (ID) information of cluster
heads to the mobile collector for optimizing the data collection tour. Third,
we deploy a mobile collector with two antennas (called SenCar in this paper) to
allow concurrent uploading from two cluster heads by using MU-MIMO
communication.

Advantages

·When
each cluster has at most two cluster heads, LBC-DDU achieves over 50% energy
saving per node and 60% energy saving on cluster heads comparing with data
collection through multi-hop relay to the static data sink, and 20% shorter
data collection time compared to traditional mobile data gathering.

·The
main advantage is to utilize distributed clustering for scalability, to employ
mobility for energy saving and uniform energy consumption, and to exploit
Multi-User Multiple-Input and Multiple-Output (MUMIMO) technique for concurrent
data uploading to shorten latency.